With the recent growth of the Internet and success of wireless network technology, the transmission of video signals has experienced a significant increase in popularity. However, most communication systems over which video signals are communicated are limited in storage and/or bandwidth capacity. Because raw video signals are often very large in size, such storage and/or bandwidth limits can render the transmission of raw video signals over such networks impracticable.
To nonetheless allow transmission of video signals over such networks, video signals can be distributed and stored in compressed format. For example, in video streaming applications, a server can generate compressed video bitstreams from a raw video signal for transmission to users. Multiple bitstreams may be generated, each with different bit rates corresponding to varying network conditions. Once the bitstreams are generated, the raw video signal can then be discarded due to storage limits. The bitstreams can then be transmitted to one or more users, after which the users can reconstruct the video signal from the received bitstreams. However, because video compression is a lossy process, the video signals reconstructed by each user will be distorted from the original raw video signal. Traditionally, when multiple bitstreams having different bit rates are available, this distortion is mitigated while reconstructing the original video by decoding the video bitstream with the highest bit rate. However, this traditional approach does not take into consideration all of the available data, such as data present in the bitstreams with lower bit rates, which could also be utilized to improve decoding performance. Accordingly, there exists a need in the art for techniques for reconstructing a video signal from video bitstreams with a higher degree of precision.